---
name: capture-api-response-test-fixture
description: Capture API response test fixture.
metadata:
  internal: true
title: capture-api-response-test-fixture
canonical_url: https://skilld.dev/gh/vercel/ai/capture-api-response-test-fixture
last_updated: 2026-09-10T04:18:40.000Z
---

> **Skill from skilld.dev.** Follow the instructions below for this session. You do not need to install anything.
>
> If the user asked to install this Skill, run `npx skilld@beta install skilld:vercel/ai/capture-api-response-test-fixture`. Install writes the Skill files into the project, so every session loads them.

### API Response Test Fixtures

For provider response parsing tests, we aim at storing test fixtures with the true responses from the providers (unless they are too large in which case some cutting that does not change semantics is advised).

The fixtures are stored in a `__fixtures__` subfolder, e.g. `packages/openai/src/responses/__fixtures__`. See the file names in `packages/openai/src/responses/__fixtures__` for naming conventions and `packages/openai/src/responses/openai-responses-language-model.test.ts` for how to set up test helpers.

You can use our examples under `/examples/ai-functions` to generate test fixtures.

#### generateText (doGenerate testing)

For `generateText`, put the script under `src/generate-text/<provider>/`, log the raw response output to the console, and copy it into a new test fixture.

```ts
import { openai } from '@ai-sdk/openai';
import { generateText } from 'ai';
import { run } from '../../lib/run';

run(async () => {
  const result = await generateText({
    model: openai('gpt-5-nano'),
    prompt: 'Invent a new holiday and describe its traditions.',
  });

  console.log(JSON.stringify(result.response.body, null, 2));
});
```

#### streamText (doStream testing)

For `streamText`, you need to set `includeRawChunks` to `true` and use the special `saveRawChunks` helper. Put the script under the provider directory and run it from the `/examples/ai-functions` folder via `pnpm tsx src/stream-text/<provider>/<script-name>.ts`. The result is then stored in the `/examples/ai-functions/output` folder. You can copy it to your fixtures folder and rename it.

```ts
import { openai } from '@ai-sdk/openai';
import { streamText } from 'ai';
import { run } from '../../lib/run';
import { saveRawChunks } from '../../lib/save-raw-chunks';

run(async () => {
  const result = streamText({
    model: openai('gpt-5-nano'),
    prompt: 'Invent a new holiday and describe its traditions.',
    includeRawChunks: true,
  });

  await saveRawChunks({ result, filename: 'openai-gpt-5-nano' });
});
```